Mid-trimester prediction of spontaneous preterm birth with automated cervical quantitative ultrasound texture analysis and cervical length: a prospective study

Abstract

The objective of this study was to evaluate a novel automated test based on ultrasound cervical texture analysis to predict spontaneous Preterm Birth (sPTB) alone and in combination with Cervical Length (CL). General population singleton pregnancies between 18 + 0 and 24 + 6 weeks’ gestation were assessed prospectively at two centers. Cervical ultrasound images were evaluated and the occurrence of sPTB before weeks 37 + 0 and 34 + 0 were recorded. CL was measured on-site. The automated texture analysis test was applied offline to all images. Their performance to predict the occurrence of sPTB before 37 + 0 and 34 + 0 weeks was evaluated separately and in combination on 633 recruited patients. AUC for sPTB prediction before weeks 37 and 34 respectively were as follows: 55.5% and 65.3% for CL, 63.4% and 66.3% for texture analysis, 67.5% and 76.7% when combined. The new test improved detection rates of CL at similar low FPR. Combining the two increased detection rate compared to CL alone from 13.0 to 30.4% for sPTB < 37 and from 14.3 to 42.9% sPTB < 34. Texture analysis of cervical ultrasound improved sPTB detection rate compared to cervical length for similar FPR, and the two combined together increased significantly prediction performance. This results should be confirmed in larger cohorts.

Artificial intelligence in obstetrics

“…The fundamental reason for this social cost expenditure on obstetric diseases is that it is difficult to predict and diagnose maternal and fetal diseases early, and therefore, even if the disease is found, the effectiveness of treatment is low. The area under the receiver operating characteristic curve (AUC) for diagnosis of conditions, such as preterm birth, preeclampsia, fetal growth restriction, and stillbirth, which are relatively common but have a significant impact on maternal and fetal health, has been reported to be 0.51-0.85, 0.61-0.99, 0.54-0.98, and 0.58-0.76, respectively [2][3][4][5][6][7][8][9][10]. Evidence-based traditional research methodologies have been the main tools used to solve problems related to obstetric healthcare.…”